From Local to Global in 2025

Full transcript

Sophie Krishnan (CEO): Hi everyone, it's great to have you here today. Britt anchored this webinar under a theme of good resolutions, so I'll share two of mine for this year: to be more focused for deep thinking, and to create fun memories with my family. Switching gears — since I joined, we've been speaking with many customers, and it's clear the localization industry is on an exciting journey, which we call our expedition at Lokalise. Today we want to share some of the main themes driving our investments and decisions as we look ahead.

Five themes shaping Lokalise's roadmap

1. More companies are localizing at scale. This starts with your customers: if your content isn't speaking your customers' own language, your go-to-market is leaving money on the table. Seventy-five percent of customers are more likely to buy from brands that communicate in their native language. At Lokalise, we're seeing many customers who were localizing manually now start to automate their localization journey.

2. A lot more automation, and speed to customers. Customers keep asking us how to scale localization effectively, and automation of both processes and tasks is the biggest ask. This isn't unique to localization — automation drives efficiency gains across the whole SaaS ecosystem — but our customers specifically report that automation can cut timelines by fifty percent. One customer told us switching to an automated workflow felt like a flip being switched, calling it "a breath of fresh air."

3. Inroads from AI in localization. There's a lot of talk about AI in the press, and in localization it's a reality. For many language pairs, large language models are now outperforming traditional machine translation, meaning translations increasingly feel authentic and human. Many customers started exploring AI translation in 2024, and that adoption is ramping up now — translation based on AI, MT, translation memory, and API-driven workflows now accounts for seventy percent of translation volume, meaning human translation is now below thirty percent.

4. More automation and AI means more need for accountability and visibility. As speed increases, leaders are asking less "how do I get this translated?" and more "how is this driving growth and value in the business?" A Slator report found that companies using real-time data see thirty percent better resource allocation and manage to cut budget by twenty-five percent.

5. The continued need for exceptional customer support and success. We've always invested in high-quality customer support with deep technical knowledge — a strong differentiator for us — and while automation makes many things easier, we believe localization is fundamentally difficult, so we remain fully committed to our support teams.

What excites me most in the months ahead is the chance to help you deliver content easily and securely to every market, language, and culture that matters to your team, so you can connect confidently with your diverse audiences. Now, Ori — our senior director of product — will share some of the solutions we've been building.

Ori Gal: what we shipped

Our customers tell us they love the platform and want us to go to the next level on a few fronts: more powerful, easier-to-configure automation; harnessing AI to speed up localization and reduce cost without compromising quality; and the ability to tangibly, objectively understand localization performance so you know what to improve. I'll walk through the specific pain points we heard and what we built to address each one.

Automation — introducing Lokalise Workflows. Many customers still rely on spreadsheets, emails, Slack notifications, and repetitive manual tasks to orchestrate localization, which leads to inefficiencies and errors — and building more sophisticated automation often required development effort and API access that not every customer has. As you scale to more languages and projects, coordinating multiple stakeholders without a centralized system can become overwhelming, with miscommunication leading to missed deadlines. Lokalise Workflows lets you set up a workflow in one place, in minutes, using intuitive predefined templates — for example, a workflow that takes translation memory, applies AI translation, and routes it to human review for quality assurance. You can configure a workflow without a single line of code, set rules for when it runs based on key updates or deadlines, batch translations with a scheduler to avoid over-notifying your team, and get full visibility into tasks, progress, and bottlenecks across projects in one place. This is a starting point — workflow capability will keep expanding across the platform.

AI quality — the next iteration of Lokalise AI. Many customers want to lean into AI more, but perceive a trade-off between speed and quality due to a lack of context, while manual translation at scale requires more people and gets expensive fast. The next iteration of Lokalise AI adheres to your glossary and style guide for brand consistency, and automatically chooses the best translation engine for your content type and context, so you get the best quality from the start. Combined with workflows, this lets people focus only on the translations that genuinely need review. Results from customers already using Lokalise AI: projects are completed ten times faster than human translation including edits, and about eighty percent cost savings compared to human translation and process management. Joaquin from Life360 translated into seven languages, a hundred thousand words per language, at eighty percent less time and cost. Romain from Florence reported AI automations getting translations right the first time eighty percent of the time.

Visibility — introducing Lokalise Analytics. Teams struggle because data is incomplete or scattered across multiple sources, making resource allocation, forecasting, and optimization largely guesswork — and as automation and AI usage grows, it becomes harder to explain what the localization team is actually spending its time on if you can't track it. Lokalise Analytics gives you dashboards covering volumes (keys added or edited), team performance (tasks created, completed, or overdue), task timelines (average time per task, words translated per day), and translation-method performance (edit rates, showing how effective a chosen method really is). This helps you spot bottlenecks, balance workload across linguists and vendors, monitor completion times against SLAs, see workload trends over time by task volume and language, and communicate effort clearly to stakeholders for future launches and campaigns. You can filter by date range and language, and — on enterprise plans — by product, stakeholder, campaign, or launch. Per the Slator research Sophie mentioned, this kind of visibility improves resource allocation by thirty percent and can lead to a twenty-five percent reduction in localization cost.

Permission management. We've also improved permission management, giving you better control over who can access what in your account — extracting more value from the platform while reducing the risk of costly errors from people accessing the wrong parts of it.

To recap: Workflows for seamless automation, Lokalise AI for faster, cheaper, higher-quality translation, Lokalise Analytics to understand and optimize your localization process, and improved permission management for better access control. We'll keep evolving all of these. Looking ahead, we'll run dedicated deep-dive webinars on each: workflows with Luke in February, Lokalise Analytics with Alex in March, and Lokalise AI with Adam in April — plus more announcements in the months ahead.

The session closed with a note that the team would follow up with more roadmap detail in future webinars and in conversations with customer success managers, and handed over to the Q&A.